Statistical Methods Using STATA

Running head: STATISTICAL METHODS USING STATA
Statistical Methods Using STATA
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STATISTICAL METHODS USING STATA
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Table of Contents
Introduction................................................................................................................................2
Details of the dataset..................................................................................................................2
Data transformation....................................................................................................................2
Data Analysis.............................................................................................................................2
Results........................................................................................................................................3
Conclusion..................................................................................................................................4
Reference....................................................................................................................................5
Appendix....................................................................................................................................6
Appendix 1: Details of the dataset.........................................................................................6
Appendix 2: Summary statistics of total self-reported earnings and also for male and female. 7
Appendix 3: T-test result............................................................................................................8

STATISTICAL METHODS USING STATA
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Introduction
Data analytics is potentially able to forecast with the help of relevant data and
statistical software. Here, the data that is used to prepare the report, was used in experimental
evolution of the Job Corps, conducted by the Mathematical Policy Research under contract to
the U.S. Department of Labour. The report tries to find the difference of earning across
gender of the individual (Geiger, 2017, Schochet, 2018 & Wandner, 2017).
Details of the dataset
The data set includes too many important variables as it was used in a crucial research
work. However, the important variables that are considered here are gender which is named
identification number (mprid), treatment group (treatment), gender (female), ethnicity
(race_eth), age group, educational group (educ_gr), earnings in the year prior to random
assignment (earn_yr) and self-reported earnings per week in the 4th year after the random
assignment (earny4).
Data transformation
The missing values and the zero values of earny4 are dropped. Treatment group is
selected for the analysis and the control group is dropped. “earny4” is transformed into
“earncen”. The values of “earncen” is equal to “earny4” where all the values were less than
300 and the remaining values of “earncen” were fixed at 300.
Data Analysis
To check the difference in earning of the male and female groups, t-test is conducted.
Before t-test the details of “earncen” is calculated for male and female.